Medical & Biological Engineering & Computing

, Volume 46, Issue 6, pp 605–611

Discovering active compounds from mixture of natural products by data mining approach

Authors

  • Yi Wang
    • Pharmaceutical Informatics Institute, College of Pharmaceutical SciencesZhejiang University
  • Yecheng Jin
    • Pharmaceutical Informatics Institute, College of Pharmaceutical SciencesZhejiang University
  • Chenguang Zhou
    • Pharmaceutical Informatics Institute, College of Pharmaceutical SciencesZhejiang University
  • Haibin Qu
    • Pharmaceutical Informatics Institute, College of Pharmaceutical SciencesZhejiang University
    • Pharmaceutical Informatics Institute, College of Pharmaceutical SciencesZhejiang University
Original Article

DOI: 10.1007/s11517-008-0323-1

Cite this article as:
Wang, Y., Jin, Y., Zhou, C. et al. Med Biol Eng Comput (2008) 46: 605. doi:10.1007/s11517-008-0323-1

Abstract

Traditionally, active compounds were discovered from natural products by repeated isolation and bioassays, which can be highly time consuming. Here, we have developed a data mining approach using the casual discovery algorithm to identify active compounds from mixtures by investigating the correlation between their chemical composition and bioactivity in the mixtures. The efficacy of our algorithm was validated by the cytotoxic effect of Panax ginseng extracts on MCF-7 cells and compared with previous reports. It was demonstrated that our method could successfully pick out active compounds from a mixture in the absence of separation processes. It is expected that the presented algorithm can possibly accelerate the process of discovering new drugs.

Keywords

Quantitative composition–activity relationshipCausalityBioassay-guided isolationDrug discoveryTraditional chinese medicine

Copyright information

© International Federation for Medical and Biological Engineering 2008